With the deployment of 4G networks, cellular operators are able to manage up to three partly overlapped different RATs (e.g., 2G, 3G and 4G (or Long Term Evolution (LTE)). In practice, the latest RAT (e.g., LTE) is usually deployed over areas completely covered by more mature technologies (e.g., 2G and 3G) and it is therefore common that coverage holes in LTE are served by other radio access technologies. To make the most of the new infrastructure, operators try to maximize time spent by users on LTE without degrading network performance and user quality of service. Thus, iRAT mobility robustness optimization has been identified as an important use case of self-organizing network by Next Generation Mobile Networks (NGNM) alliance and 3rd Generation Partnership Project (3GPP).
In LTE, iRAT HO is typically initiated when the measured signal level from the serving cell (given by Reference Symbol Received Power, RSRP) is lower than a certain threshold. By tuning this signal-level threshold, it is possible to decide how long users are kept on LTE before sending them to another RAT. The aims of most self-tuning algorithms for iRAT HO parameters in recently deployed RATs include: a) to keep users as long as possible in the new technology (in this case, LTE), while not degrading their connection quality excessively, and b) send users experiencing degraded connection quality to other technologies before connection quality becomes too low. In this context, it is essential to have a performance indicator that indicates, for each cell, if users are being sent to other RATs too early or too late. More importantly, such a performance indicator should give an indication of potential connection quality problems due to iRAT HO before problems occur.
Currently, widely used high level performance indicators (e.g., Retainability, HO Success Rate, etc.) could be used to detect if users are being sent to other technologies too early or too late. Keeping users too long on LTE should degrade these performance indicators and sending it to early should improve them. Therefore, they can be considered to know iRAT HO performance.
In Awada et al. “A SON-Based Algorithm for the Optimization of Inter-RAT Handover Parameters” an algorithm is proposed for optimizing iRAT HO parameters in each cell. As a measurement of iRAT HO performance from LTE to 3G, it proposes (among others): a) the number of User Equipment (UE) drops before an iRAT HO is initiated or executed from LTE to 3G (referred to as Too Late iRAT HO (TLIH)), and b) the number of UEs that reconnect again to LTE just after they have triggered an iRAT HO to 3G (referred to as Too Early iRAT HO (TEIH)). Such a categorization of radio link failures due to iRAT HO was already performed by 3GPP in TS 32.425.
In Awada et al. “A location-based self-optimizing algorithm for the inter-RAT handover parameters” and in WO2013020584, there is proposed a new category of iRAT HO, namely unnecessary iRAT HO (UIH). An iRAT HO is determined to be UIH if, after the handover from LTE to 3G, the signal quality of the old LTE cell is still higher than a certain threshold for a defined time interval. Signal quality is measured by means of the Reference Signal Received Quality (RSRQ).
In WO2010121418, a method for detecting HO problems by measuring link quality when a HO is performed is proposed. In the method, at least one measurement of link quality between the terminal and any of the base stations must be taken at the end of a successful HO, which is later analyzed to detect a HO problem. WO2010121418 specifies that the system must include at least a first radio base station, a second radio base station and a mobile terminal able to communicate with both base stations.
Whilst the above refers to iRAT-HO and corresponds to a sort of inter-system handover between one system and another, there are other concerns more specific of HO between different cells of a particular system, namely intra-HO.
In intra-HO scenarios, Load Balance (LB) algorithms based on tuning handover parameters is known as Mobility Load Balancing (MLB) and has been widely used in different RATs. In particular, MLB has been identified in LTE as an important use case of Self-Organizing Networks (SONs). MLB is carried out by triggering intra-HOs from congested cells to less loaded cells earlier and delaying intra-HOs from less loaded cells to congested cells. This effect can be achieved by adjusting intra-HO margins between adjacent cells, defining by how much the pilot signal level received from the new cell has to exceed that of the serving cell to trigger the intra-HO. Such an adjustment can be done on a per-adjacency basis, i.e. per each couple of source and target cells.
However, MLB with adjusting (changing) intra-HO margins from respective default values have proved in field trials the impairment of connection quality. For example, an issue with load balancing is acute for users travelling from an ‘empty’ cell to a ‘congested’ cell, wherein intra-HO is delayed since: i) the congested cell has a larger utilization of radio resources and the probability that a user in the empty cell collides with other user in the congested cell is very high; and ii) the cell border between both cells get closer to the congested cell.
In the past, some solutions have been applied to avoid connection quality problems associated to MLB:                1) Detection from HO Failure Ratio. Using HO failure ratio to decide when HO parameters can be modified is common practice. HO failure ratio is calculated as the ratio between the numbers of HO failures and the total number of HOs in a per adjacency basis. Thus, MLB will be only applied in adjacencies where HO failure ratio is not high, in the hope that this will avoid degradation in high level indicators (e.g., retainability, and HO failure ratio).        2) Detection by classification of HO failures. 3GPP TS 32.521 defines two types of HO failures: 1) Too Late HOs, which are HOs failures due to too late HO triggering, and 2) Too early HOs, corresponding to HOs failures due to too early HO triggering. Both indicators can be measured on a per-adjacency basis. As a measure of HO quality, these indicators can be used to detect problems in HO margins, and can thus be used to stop MLB in certain adjacencies. Specifically, adjacencies where the number of too early HOs (or too late HOs) would not bring forward (or delay) HO by tuning HO parameters.        3) Avoidance by tuning HO signal-level constraints. In Toril & Wille “Optimization of Handover Parameters for Traffic Sharing in GERAN”, a self-tuning method is proposed to jointly optimize HO margins, HO signal-level constraints and cell reselection offsets for congestion relief. Increasing signal-level constraints on outgoing adjacencies includes additional constraints on the HO, which delays the HO. When signal-level constraints are large enough, a minimum connection quality is enforced in HOs from the congested cell to the adjacent cell. Such a restriction on HO should only be done when HO margins become negative and the target cell in the adjacency could be highly interfered, which is the case after MLB.        4) Detection/avoidance by adaptation of HO margin step by reinforcement learning. In Mwanje & Mitschele-Thie “Minimizing Handover Performance Degradation Due to LTE Self Organized Mobility Load Balancing”, a Q-learning algorithm is proposed to find the best change in the HO margins when a cell is congested in a LTE network. The aim of the algorithm is to reallocate users to solve congestion problems with minimum impact on connection quality performance. For this purpose, during an exploration phase, the algorithm performs different changes of HO margins and evaluates the impact of every change on network performance in terms of cell load and too early HO probability. Those HO margin settings causing high radio link failures due to too early HO are given a penalty, so that they are finally discarded.        5) Method for HO problem identification. In WO2010121418, a method is proposed for detecting HO problems by measuring link quality when a HO is performed. In the method, at least one measurement of link quality between the terminal and any of the base stations must be taken at the end of a successful HO or between a time of a handover trigger and a time of a handover execution completion, which is later analyzed to detect a HO problem.        
In the above discussion, several performance indicators have been introduced as a measurement of iRAT HO performance. A first group of performance indicators, consisting in widely used high level performance indicators (e.g. Retainability, HO Successful Rate, etc.), have an important limitation. Degradation in some of these performance indicators could be caused by other reasons than a bad configuration of iRAT HO parameters, and thus, they are difficult to use as a measurement of iRAT HO performance.
A second group of performance indicators, consisting of TLIH and TEIH proposed in Awada et al. “A SON-Based Algorithm for the Optimization of Inter-RAT Handover Parameters” have several important limitations. TLIHs and TEIHs can be caused for different reasons than LTE channel quality problems (e.g., cell congestion, 2G/3G channel quality problems . . . ). Likewise, TLIH (and TEIH) counts as a UE drop (or reconnection), which means that the problem is already present in the network (i.e., it has been detected too late), and it would be desirable to detect potential connection quality problems during iRAT HO before these take place.
The UIR indicators proposed in Awada et al. “A location-based self-optimizing algorithm for the inter-RAT handover parameters” and in WO2013020584 detect unnecessary iRAT HOs, but have two important limitations:                1) UIR is based on RSRQ measurements, and it is therefore only focused on DL channel. In large LTE cells, where the number of iRAT HOs is usually higher, cell edge performance is given by UL channels, which experience worse performance than DL channels due to the UE transmission power limitation. Thus, it is very important to check UL channel quality before an iRAT HO.        2) UIR only detects good performance previously to an iRAT HO, what would allow delay iRAT HO and keep users on LTE longer (note that performance is based only on DL channel). However, it would be desirable to detect also poor channel quality in LTE, so that iRAT HOs is triggered earlier (i.e., iRAT HO point is brought forward), avoiding potential drops before iRAT HO is triggered. This problem could be solved by using TLIH to complement UIR, but this counter, as has been already explained, presents some limitations.        
Finally, the method proposed in WO2010121418 describes a general framework for detecting HO problems based on measurements of link quality taken at the end of a successful HO or between a time of a handover trigger and a time of a handover execution completion.
Furthermore, previous solutions that have been applied to avoid connection quality problems associated to MLB also have some limitations that proposed solution tries to overcome. For different reasons, the above-described solutions cannot be used in the MLB algorithm in the SON OM tool for LTE.
The use of HO failure ratio as a brake of MLB algorithm has important limitations. First, a large HO failure ratio can be due to different reasons, which may not be related to channel quality degradation caused by MLB (e.g., congestion problems and/or control channel problems). Only HO failure caused by channel conditions during HO process should be taken into account, since MLB algorithm will affect directly the channel quality. Secondly, and perhaps most importantly, a large HO failure ratio means that connection quality has already been degraded excessively, since a high-level performance indicators (e.g., HO failure ratio) is negatively affected. Although HO failure ratio is a potential HO performance indicator to use as MLB brake, it would be desirable to have an indicator that detects poor HO performance due to channel quality problems before HO failures occur. Finally, HO failure rate may be caused by bad connection quality in UE-SC (User Equipment-to-Source Cell) or UE-TC (User Equipment-to-Target Cell) links. Thus, it is not possible to know which link is the cause of HO failures.